Abstract:
The majority of microarray studies focus on analysis of gene
expression differences between various specimens or
conditions. However, the causes of this variability from one
cancer to another, from one sample to another and from one
gene to another often remain unknown. In this study, we
present a systematic procedure for finding genes whose
expression is altered due to an intrinsic or extrinsic
explanatory phenomenon. The procedure consists of three
stages: preprocessing, data integration and statistical
analysis. We tested and verified the utility of this approach
in a case study, where expression and copy number levels of
13,824 genes were determined in 14 breast cancer cell lines.
The procedure resulted in identification of 92 genes whose
gene expression levels could be explained by the variability
of gene copy number. This set includes several genes that are
known to be both overexpressed and amplified in breast
cancer. Thus, these genes may represent an important set of
primary, genetically altered genes that drive cancer
progression.